Key Skills

Job Description

The Senior Data Engineer is responsible for owning key data topics across products, including dataset creation, data export, annotation workflows, and performance monitoring, and for driving those topics end to end. This role makes structuring decisions on team tooling and data architecture, builds reusable pipelines and automation, and mentors more junior data team members. Work is done with radiologists, product managers, AI engineers, clinical research scientists, and data engineers to support medical product development. Essential Duties And Responsibilities Own one or several data topics across products, such as dataset creation, data export, annotation workflows, and performance monitoring, and drive them end to end. Design and maintain reusable tooling, including pipelines, dashboards, and automation, for the data team and for stakeholders who need to access, explore, or use the data. Make structuring decisions on technical implementation, team tooling, and data architecture, and maintain codebase quality and process efficiency. Surface actionable insights from the data lake by identifying, structuring, and delivering relevant information to product, AI, and clinical stakeholders. Drive the targeting and collection of relevant data. Build and structure medically consistent and representative datasets. Establish annotation guidelines and training so annotation quality stays consistent. Contribute to ongoing oversight and refinement of AI algorithm performance. Mentor more junior data team members through technical guidance and knowledge sharing. Write automated tests and apply code versioning and review standards to data processes and tools. Minimum Qualifications, Education And Experience Master's degree in a health-related or scientific field (required). 5+ years of relevant experience in data management, data engineering, or data science, ideally in healthcare or medical imaging (required). Excellent proficiency in Python and database query languages, and comfort working with databases such as BigQuery and MongoDB (required). Ability to structure, document, industrialize, and optimize data processes and tools (required). Experience writing automated tests and working with code versioning and review (required). Knowledge of medical imaging and of how data and annotations shape AI algorithm development (required). Strong reasoning, attention to detail, and an analytical and scientific mindset (required). Ability to translate needs between technical and less technical stakeholders and to mentor others (required). Ability to manage multiple topics in parallel while maintaining a broader view of product and data priorities (required). Preferred: Machine learning understanding. Preferred: Experience with medical device development Quality Standards Communicates, cooperates, and consistently functions professionally and harmoniously with all levels of supervision, co-workers, visitors, and vendors. Demonstrates initiative, personal awareness, professionalism and integrity, and exercises confidentiality in all areas of performance. Follows all local, regional and country laws concerning employment. Follows all DeepHealth policies and procedures. Follows data privacy, compliance, safety and confidentiality standards at all times. Practices universal safety precautions. Promotes good public relations on the phone and in person. Adapts and is willing to learn new tasks, methods, and systems. Reports to work regularly as scheduled; consistently punctual with respect to working hours, meal and rest breaks, and maintains satisfactory personal attendance in accordance with DeepHealth guidelines. Completes job responsibilities in a quality and timely manner. Travel This position may require occasional travel. Working Environment Office / Hybrid. Paris or Netherlands. Physical Demands The employee must be able to perform the essential duties and responsibilities of the position, with or without reasonable accommodation.

Core Responsibilities

The Senior Data Engineer will own end-to-end data topics including dataset creation, annotation workflows, and performance monitoring. They will also design reusable data architecture, build automation tools, and mentor junior team members to support medical product development.

Requirements

Candidates must hold a Master's degree in a scientific or health-related field and possess at least 5 years of experience in data engineering or data science. Proficiency in Python, database management, and knowledge of medical imaging or AI development is required.